In this study,we solve the finite-time leader-follower consensus problem of discrete-time second-order multi-agent systems(MASs)under the constraints of external disturbances.First,a novel consensus scheme is designed...In this study,we solve the finite-time leader-follower consensus problem of discrete-time second-order multi-agent systems(MASs)under the constraints of external disturbances.First,a novel consensus scheme is designed using a novel adaptive sliding mode control theory.Our adaptive controller is designed using the traditional sliding mode reaching law,and its advantages are chatter reduction and invariance to disturbances.In addition,the finite-time stability is demonstrated by presenting a discrete Lyapunov function.Finally,simulation results are presented to prove the validity of our theoretical results.展开更多
This work deals with the development of a decentralized optimal control algorithm, along with a robust observer,for the relative motion control of spacecraft in leader-follower based formation. An adaptive gain higher...This work deals with the development of a decentralized optimal control algorithm, along with a robust observer,for the relative motion control of spacecraft in leader-follower based formation. An adaptive gain higher order sliding mode observer has been proposed to estimate the velocity as well as unmeasured disturbances from the noisy position measurements.A differentiator structure containing the Lipschitz constant and Lebesgue measurable control input, is utilized for obtaining the estimates. Adaptive tuning algorithms are derived based on Lyapunov stability theory, for updating the observer gains,which will give enough flexibility in the choice of initial estimates.Moreover, it may help to cope with unexpected state jerks. The trajectory tracking problem is formulated as a finite horizon optimal control problem, which is solved online. The control constraints are incorporated by using a nonquadratic performance functional. An adaptive update law has been derived for tuning the step size in the optimization algorithm, which may help to improve the convergence speed. Moreover, it is an attractive alternative to the heuristic choice of step size for diverse operating conditions. The disturbance as well as state estimates from the higher order sliding mode observer are utilized by the plant output prediction model, which will improve the overall performance of the controller. The nonlinear dynamics defined in leader fixed Euler-Hill frame has been considered for the present work and the reference trajectories are generated using Hill-Clohessy-Wiltshire equations of unperturbed motion. The simulation results based on rigorous perturbation analysis are presented to confirm the robustness of the proposed approach.展开更多
基金Project supported by the National Natural Science Foundation of China(Nos.61873300 and 61722312)the Fundamental Research Funds for the Central Universities,China(Nos.FRFMP-20-11 and FRF-IDRY-20-030)。
文摘In this study,we solve the finite-time leader-follower consensus problem of discrete-time second-order multi-agent systems(MASs)under the constraints of external disturbances.First,a novel consensus scheme is designed using a novel adaptive sliding mode control theory.Our adaptive controller is designed using the traditional sliding mode reaching law,and its advantages are chatter reduction and invariance to disturbances.In addition,the finite-time stability is demonstrated by presenting a discrete Lyapunov function.Finally,simulation results are presented to prove the validity of our theoretical results.
文摘This work deals with the development of a decentralized optimal control algorithm, along with a robust observer,for the relative motion control of spacecraft in leader-follower based formation. An adaptive gain higher order sliding mode observer has been proposed to estimate the velocity as well as unmeasured disturbances from the noisy position measurements.A differentiator structure containing the Lipschitz constant and Lebesgue measurable control input, is utilized for obtaining the estimates. Adaptive tuning algorithms are derived based on Lyapunov stability theory, for updating the observer gains,which will give enough flexibility in the choice of initial estimates.Moreover, it may help to cope with unexpected state jerks. The trajectory tracking problem is formulated as a finite horizon optimal control problem, which is solved online. The control constraints are incorporated by using a nonquadratic performance functional. An adaptive update law has been derived for tuning the step size in the optimization algorithm, which may help to improve the convergence speed. Moreover, it is an attractive alternative to the heuristic choice of step size for diverse operating conditions. The disturbance as well as state estimates from the higher order sliding mode observer are utilized by the plant output prediction model, which will improve the overall performance of the controller. The nonlinear dynamics defined in leader fixed Euler-Hill frame has been considered for the present work and the reference trajectories are generated using Hill-Clohessy-Wiltshire equations of unperturbed motion. The simulation results based on rigorous perturbation analysis are presented to confirm the robustness of the proposed approach.
